Transport CO2 Emissions Research Articles

Investigating the role of green transport, environmental taxes and expenditures in mitigating the transport CO2 emissions

ABSTRACT Transportation sector is considered a major contributor to the release of the carbon emissions in the atmosphere. The present research explores the effect of traffic, environmental taxes and expenditures on transport-related carbon emissions. We apply a cross-sectional autoregressive distributed lags estimator for short- and long-run estimates by using panel data for 35 OECD countries. We demonstrate traffic increase transport-related carbon emissions by 14.65% on average. Transport-related carbon emissions will rise by 1.5% over the near term as a result of the combined effect rail and road-vehicles, and energy consumption. Environmental expenditures and green transportation, on the other hand, will cut transportation emissions by 21.7% and 45.20% in the short and long runs, respectively. Furthermore, the findings reveal an inverted u-shaped link between transportation-related carbon emissions and consumption. Based on real-world evidence, this study advises that some countries reduce traffic while simultaneously increasing spending on the development of environmentally friendly transportation options.

The impacts of the COVID-19 pandemic on surface passenger transport and related CO2 emissions during different waves

The coronavirus pandemic has severely impacted our day-to-day activities and brought about significant change in all major sectors, especially surface passenger transport. Lockdowns and stay-at-home restrictions have significantly reduced energy demand and consequently CO2 emissions of surface passenger transport. The change in CO2 emissions is calculated from near-real-time activity change data as a function of 3 confinement levels. The activity change and related emission trends reflect changes in the mode of transport during different waves, this can be used to understand mobility trends and patterns when stringent measures are imposed. Consequently, constructive use of this data can help prepare and develop the transport sector in case of another epidemic outbreak or other unprecedented calamities and to build a resilient transport infrastructure post-COVID-19. This study estimates and analyzes the changes in CO2 emissions associated with the public (bus and rail) and private surface passenger transport from March 1st, 2020 to Jan 31st, 2021 in 21 countries. The research period covers the 1st and the 2nd waves of COVID-19 in these countries. A higher activity reduction and consequently CO2 emission reduction is displayed during the 1st wave compared to the 2nd for most countries despite implementing stringent measures during both waves. This is in line with countries adapting to the ‘new normal’ and restarting socio-economic activities. Similarly, public transport recovery is slower than private transport recovery, making it essential to focus on reinforcement and adaptation of public transport infrastructure for the future. The results show that a cumulative 510 Mt CO2 has been reduced over 11 months in 21 countries, compared to pre-pandemic levels. This reduction brings about a 6% drop in transport CO2 emissions and a 1.5% drop in global CO2 emissions. This analysis sheds light on mobility trends and travel behavior of surface passenger transport modes and related CO2 emissions in different countries which can be used to exemplify the path to recovery based on near-real-time data.

Research on vehicle renewable energy use in cities with different carbon emission characteristics

Different cities have significant variations in terms of economic development, population size, geographical features, energy endowment, and total amount and structure of carbon dioxide (CO2) emission from transport. It is essential to understand the types and characteristics of urban transport CO2 emissions and propose differentiated CO2 emission reduction measures and formulate renewable energy use strategy, with a view to sequentially achieving the peak of urban transport CO2 emissions. Based on the analysis of driving factors of urban transport CO2 emission, this paper establishes a classified index system and then adopts the Gaussian mixture model (GMM) and expectation–maximization (EM) algorithm to cluster the trends of transport CO2 emissions peak in 672 municipal cities in China. The results show that the model can effectively identify the differences between different cities and divide them into five types, namely the types of public transport demonstration, emission pressure, low carbon potential, population loss, and high carbon pressure, the proportion of urban transportation carbon emission in these five cities is 44.39%, 22.19%, 18.21%, 7.66% and 7.55%. Moreover, by analyzing different energy endowment characteristics and geographical features, optimization suggestions are put forward for the transportation energy consumption of different cities to realize the efficient utilization of renewable energy.

Optimisation of Logistic Model Using Geographic Information Systems: A Case Study of Biomass-based Combined Heat & Power Generation in China

Biofuel large-scale application was constrained due to cost control. In order to reduce biofuel production cost and increase profitability, long-term strategy (strategic) and medium-term strategy (tactical) combined logistic model were assessed in this study. Geographic information system has been integrated into logistic model to minimize the effect of uncertainty on logistic modelling accuracy, with aims of transferring uncertainty problem to be certain. Combined heat and power generation plant as a case study present in logistic model, which provide a method in plant location and capacity selection criteria; logistic model design; and interaction between logistic model and local conditions. The logistic plan with compression as a pre-treatment technology has the optimal profitability performance, their properties affect the selection of the transport route, especially optimal for a lower availability of agricultural residues. With increased availability, torrefaction turns to more efficiency biomass pre-treatment technology due to storage cost significant reduction. With geographic information system transportation route assistance, logistic model transportation cost and CO2 emission has a 0.02% and 0.01% reduction.

Energy Consumption from Transport Sector and CO₂ Emission: A Case of Kandahar City

This paper is concerned with the prospective estimation of energy consumption in the transport sector. To determine the long-term energy consumption targets for transport in Kandahar city. Later on CO2 emission is calculated based on energy consumption in transport sector of Kandahar city from year 2017 to 2020 and the amount of emission is forecasted till 2030. Upon conducting this research it is found out that transport demand has increased during the last few years due to change in population growth and GDP. As a result, traffic congestion, road accidents, parking problems and air quality are worsening. In addition to those, lack of proper transport management system, public transport infrastructure and insufficient road capacity are adding growing energy demand and environmental problems of Kandahar transport sector. In order to avoid such problems, this research is conducted to focus on the energy demand and CO2 emission only in transport sector of the Kandahar city.
 This study has focused on energy demand and emission of CO2 from passenger transport sector of Kandahar city from 2017 to 2020. If there is no policy intervention, energy demand can reach from 5.5 TJ in 2017 up to 14.8 TJ in 2030. Again gasoline passenger vehicles contributes the most in energy demand and emission. CO2 emission can reach from 381 Thousand metric tons in 2020 up to 860.9 Thousand metric tons in 2030.
 Out of all vehicle types of transportation, private cars are responsible for 26% of energy share, motorbikes consuming the most and reaching up to 35%.

Use of GPS-data to improve transport solutions in a cost and environmental perspective

In this paper we have utilised GPS data as a base to track truck movements and analyse transport activities. Combined with a Decision Support Tool we have investigated how different transport solutions affect the transport cost and CO2 emissions. The information gained from GPS-data helps firms such as a fruit and vegetables wholesaler to gain better insights into their transport solution and operations from a cost and environmental perspective. This also means that the current analysis remains useful for the transporting company in making strategic decisions as to when and where they should engage in other transport assignments to improve the load factors on their trucks.This paper presents that the picture the decision-makers had prior to GPS data being used was different from the real situation, and the insights gained lead to new knowledge and actions. As a result, this would contribute to greener and more cost-efficient solutions.

Testing the heterogeneous effect of air transport intensity on CO2 emissions in G20 countries: An advanced empirical analysis.

This study investigates the heterogeneous impact of air transport intensity, air passenger transport, and air freight transport onair transport carbon emissionsin G20 countries for the period of 1990-2016. The paper employs a robust and advanced fixed-effect panel quantile regression model that considers unobserved discrete and distributional heterogeneity. Our empirical results show that the impact of the independent variables on air transport carbon emissions is quite heterogeneous across various quantiles.More specifically, the effect of air transport intensity, air passenger transport, and air freight transport on carbon emissions is positive and becomes more assertive with the increasing trend at upper quantiles and is quite heterogeneous across all quantiles. Economic growth, urbanization, and tourism are significant contributing factors in enhancing air transport CO2 emissions, while crude oil price significantly reduces CO2 emissions. The Dumitrescu and Hurlincausality test estimates indicate that a bidirectional relationship extends from air transport intensity, air passenger transport, and air freight transport to air transport CO2 emissions. The findings underline the need for cleaner, renewable, and environmentally sustainable energy sources for air transport operations.

Multi-Objective Modeling of Relief Items Distribution Network Design Problem in Disaster Relief Logistics Considering Transportation System and CO2 Emission

The present study aims to propose a multi-objective mixed integer mathematical programming model for designing a relief items distribution network in sustainable disaster relief logistics. The first objective function minimizes the total network costs. Which are divided into two parts: 1- relief costs including (transportation costs, inventory costs and fixed costs of facilities) 2- social costs (deprivation cost). The second objective function minimizes the amount of pollution generated by the network. Considering the related literature review, this is the first study that to propose a robust fuzzy optimization approach for relief items distribution network design problem considering environmental (CO2 emission), social (deprivation cost) and economic impacts under reliability and uncertainty. Then, the multi-objective model was solved using the multi-choice goal programming. To indicate the validity of the proposed model, a case study was evaluated based on real data (2019 flood in Sari city, Mazandaran Province). Using the proposed model, decision-makers and managers are able to make strategic and tactical decisions with the least cost and time, and in relief planning can enhance the structure of distribution networks and inventory and reduce victims’ dissatisfaction.

Assessing the transition to low-carbon urban transport: A global comparison

The transition toward low-carbon urban transport is essential for achieving the global goal of “carbon neutrality”. However, a global comparison of urban transport CO2 emissions is still insufficient due to the lack of comprehensive, comparable, and consistent data on transport at the city level. To assess the transition to low-carbon urban transport globally, this study measures the total CO2 emissions, CO2 emissions per capita, and CO2 emissions per GDP of urban transport in 180 global cities using a unified method based on extensive data collected in 44 countries across 6 continents from 1960 to 2012. Then, the regional disparity and historical trend of the three indicators are analyzed to characterize the transition to low-carbon urban transport. Finally, the transition progress of low-carbon urban transport in the 180 cities is assessed with a multiphase framework that consists of pre-development phase, take-off phase, acceleration phase, and stabilization phase. The results show that the changing patterns of urban transport CO2 emissions vary across continents. There is a common trend that the peak times of CO2 emissions per GDP, CO2 emissions per capita, and total CO2 emissions usually occur in sequence. Historically, cities in North America began the low-carbon transition earliest, followed by cities in Oceania, Europe, and Asia. Currently, the transition progresses in most developing cities are relatively slow and are still at the take-off phase of transition. Overall, this study can help cities better manage the transition to low-carbon urban transport for the goal of “carbon neutrality”.

CO2 Emissions and The Transport Sector in Malaysia

Transport is an essential infrastructure for development. With its high share of gross domestic product (GDP), it makes a significant contribution to total CO2 emissions in Malaysia. It is therefore important to pay greater attention to reducing CO2 emissions and sustainable development in this sector. Therefore, this study aims at estimating the relationship between transport CO2 emissions and its key drivers using the Autoregressive Distributed Lag (ARDL) technique. The time period covered by the study extends from 1978 to 2018. It further investigates the response of CO2 emissions to shocks in the value of other variables by employing the generalized impulse response approach. The results suggest that urbanization is the major contributor to the increase in CO2 emissions followed by the carbon intensity of energy in the long-run. Carbon intensity of energy, GDP per transport worker and urbanization contribute significantly to increases in transport CO2 emissions in the short- and long-run. Testing the Environmental Kuznets Curve (EKC) hypothesis recommends that Malaysia continue to be on track to reach the highest level of income and welfare to give pay more attention to the environment. Therefore, the country maintains its CO2 emissions level in the future because of economic development. Therefore, these findings show that energy and environmental policymakers need to pay more attention to improving energy efficiency and the use of low-carbon technologies and electrification in the transport sector and the use of high-quality public transport, particularly in urban areas, for sustainable urban development.

CO2-to-Fuel – Business and Institutional Aspects of Implementation Dynamics

Abstract Valorization of CO2 captured from industrial processes is an important task for reaching climate and energy targets. The presented study addresses the use of CO2 for the production of ethanol, which can be used as a transport fuel. Hydrogen, produced by renewable energy technologies, is combined with CO2 to produce the synthetic fuel, thus making this approach attractive from a climate perspective. Aim of the study was to simulate the dynamics of the development of CO2-to-fuel solution, taking Latvia as the case. System dynamics modelling was used as the method for analysis. The model reflects several important feedbacks, such as relation between the captured CO2 emissions and the share of avoided CO2 emissions in transport due to fuel substitution, as well as investment in new production capacity of the ethanol. Use of avoided CO2 emission costs for funding of research and development (R&D) of the technology and direct subsidies for ethanol production is the analysed institutional aspect. The results show that if 15 % of the industrial CO2 emissions are used for ethanol production then circa 12 % of the transport CO2 emissions can be avoided. The share of avoided transport CO2 emissions are the most sensitive to unit costs of hydrogen production.

THE CHALLENGES AND ENVIRONMENTAL JUSTIFICATION OF RECYCLING Li-ION ELECTRIC VEHICLES BATTERIES

Efforts to reduce CO2 emissions in road transportation will lead to an estimated thirtyfold increase of the number of EVs by 2030, and consequently an estimated 12.85 million tons of Li-ion batteries from EVs will go offline between 2021 and 2030. Therefore, end-of-life, waste management schemes should be put in place to success-fully deal with the battery ‘waste’. Knowing full well that bringing down the levels of GHG emissions in the atmosphere is the only way to truly mitigate the destructive effects of climate change and the recycling industry has an important role to play in the effort, this paper aimed at reviewing different Li-ion EV battery recycling procedures. The findings showed that recycling Li-ion batteries helps prevent the shortage of critical minerals from a mass flow perspective, however, from an environmental perspective, the current available technologies are not recommended to recover the base materials from Li-ion batteries since they lead to more consumption of energy and higher air emissions than primary production.

Optimization of transport costs and CO2 emissions reduction policies in a continuous cycle supply chain: case study

In this paper we analyze a distribution network and a waste collection network that adopt the same fleet of vehicles. This fleet is owned by a company that provides logistics and transport services in the Algerian territory. The objective of this work is to propose a logistics chain in circular economy (continuous cycle) by combining the transports of the two studied networks, taking advantage of the empty returns, in order to minimize the travel costs and to reduce the CO2 emissions. The purpose of this study is to investigate the impact of optimal vehicle usage in distribution networks and its influence on total supply chain costs and environmental effects.

Examination of the Share of Medium and Heavy Trucks in the SR

Abstract The state of the environment is deteriorating due to human activity. Today, almost no major international forum can avoid addressing environmental issues. Environmental protection has therefore become a mandatory issue for every responsible politician. In addition to contributing to economic growth, the role of road transport should be to ensure sustainable transport and solutions for people and goods around the world. The European Parliament has adopted Directive 2019/1161 on the promotion of environmentally friendly and energy-efficient road transport vehicles, which defines the obligations and forms of support for the procurement of environmentally friendly vehicles. In addition to these transport tasks, there is also a challenge to reduce CO2 emissions in transport through the use of new technologies in transport. Also in road freight transport, there are currently vehicles that use alternative fuels with a more favorable environmental impact. In connection with the current EU legislation, which aims to increase the share of these vehicles, attention is paid to the contribution of this area, analysis and examination of the current situation with trucks with alternative propulsion.

Pioneers of electric mobility: Lessons about transport decarbonisation from two bay areas

Electric mobility has the potential to spearhead transport decarbonisation. While there is a vast literature on the potential benefits of electric vehicles (EVs) towards sustainability and national policies of EV adoption, regional and local polices are often overlooked. Hence, this paper aims to capture lessons learned from two bay areas, namely the Guangdong-Hong Kong-Macau Greater Bay Area (GBA) in China and the San Francisco Bay Area (SFBA) in the United States. These two regions are pioneers in electric mobility within the two largest economies of the world. An integrative methodology of transport decarbonisation and backcasting analysis are applied to analyse the progress achieved so far (2000–2018) and to project future carbon reduction potentials (2019–2050). Regional and local transport CO2 emissions are estimated by a distance-based approach. The results illustrate that electric mobility has led to carbon reductions of 1.73 Mt CO2 and 0.25 Mt CO2 in 2018 in GBA and SFBA respectively, contributing to a relative decoupling status in both regions (e = 0.85 &e = 0.14). Intra-regional variability in decoupling status is observed, with stronger spatial variations in GBA. The backcasting analysis suggests that the EV share needs to reach almost 100% before 2035 so that the 450 Delayed Action vision can be achieved. This requires a proactive policy package of cleaner electricity with emissions performance standards, EV sales mandates, expanded public charging infrastructure, and a range of measures to incentivize EV market uptakes. Major driving forces of decoupling, including vehicle kilometre travelled, public transport share, and regional/local EV policies, are also identified and discussed.

Mathematical Programming and Solution Approaches for Transportation Optimisation in Supply Network

The problem of transport is a special type of mathematical programming designed to search for the optimal distribution network, taking into account the set of suppliers and the set of recipients. This article proposes an innovative approach to solving the transportation problem and devises source codes in GNU Octave (version 3.4.3) to avoid the necessity of carrying out enormous calculations in traditional methods and to minimize transportation costs, fuel consumption, and CO2 emission. The paper presents a numerical example of a solution to the transportation problem using: the northwest corner, the least cost in the matrix, the row minimum, and Vogel’s Approximation Methods (VAM). The joint use of mathematical programming and optimization was applicable to real conditions. The transport was carried out with medium load trucks. Both suppliers and recipients of materials were located geographically within the territory of the Republic of Poland. The presented model was supported by a numerical example with interpretation and visualization of the obtained results. The implementation of the proposed solution enables the user to develop an optimal transport plan for individually defined criteria.

Impacts of reducing air pollutants and CO2 emissions in urban road transport through 2035 in Chongqing, China

The road transport sector in megacities is confronted with pressing local air pollution and carbon dioxide (CO2) control issues. To determine effective policy instruments for saving energy and the co-control of air pollutants and CO2, several mainstream measures were examined and compared in Chongqing's road transport sector from 2017 to 2035. An integration assessment framework was developed by combining the Long-range Energy Alternatives Planning (LEAP) system and a set of quantitative methods for evaluating the co-benefits of emission reductions (including the air pollutant equivalent (APeq), co-control coordinate system, and pollutant reduction cross-elasticity (Elsa/b)). Results showed that the shifting transportation modes scenario presented the most significant potential for energy-saving and emission reductions, reducing energy use by 30.9% and air pollutants and CO2 emissions by approximately 27–32% compared with the business as usual (BAU) scenario in 2035. The improving energy efficiency scenario also provided significant co-benefits for reducing air pollutants and CO2 emissions. Nevertheless, the promoting alternative fuel scenario may increase fine particulate matter (PM2.5) emissions by 2.2% compared to BAU in 2035 under the cleanness of regional electricity in 2017. Our findings suggest that the shifting transportation modes were effective measures to reduce air pollutants and CO2 in the short term synergistically, and highlighted the importance of cleaner electricity generation to develop electric vehicles in the medium and long term.

Analysis of Retrofit and Scrappage Policies for the Indian Road Transport Sector in 2030

In India, the road transport sector contributed around 90% of total transport CO2 emissions in 2018. Air pollution from the road transport sector has detrimental effects on both air quality and human health. The policies implemented have a long-term impact on the amount of vehicle emissions and characteristics of fleet vehicles. The present study analyzes emissions from India’s road transport sector using the bottom-up activity approach model. Future vehicle stocks in India are projected up to 2030 using a hybrid growth model approach. Vehicle emissions of CO2, CO, particulate matter (PM), and NOx are analyzed for India's reference (2020) and projected years fleet (2030). The emissions from the projected fleet are subjected to different mitigation scenarios such as retrofit and scrappage policies to estimate the emission reduction potentials of these scenarios from the future fleet of India. The analysis of the study indicates that the retrofit policies are more effective in reducing vehicle emissions than the scrappage policies. Retrofit policies such as the advancement in emission norms (shift to Bharat Stage (BS)-VI from BS-IV), the increased share of compressed natural gas (CNG) vehicles, and fuel efficiency (FE) improvements have reduced vehicle emissions significantly compared to the scrappage of old vehicles from the fleet. The low impact of scrappage policies is attributed to the projected fleet’s lower share of old vehicles (10–15%). While retrofit policies have a significant impact as they largely affect 85% to 90% of young vehicles (less than ten years of age) in 2030. A combination of both policies is suggested to control future fleet emissions. The study also conducts sensitivity analysis, which indicates a significant influence of the emission factors in the vehicle emission analysis and GDP growth rates in the vehicle fleet projection.

Incorporating uncertainties towards a sustainable European energy system: A stochastic approach for decarbonization paths focusing on the transport sector

According to the Paris Agreement, the European energy system transition is essential to achieve GHG emission reduction targets set by the EU and limit the growth of global temperatures. Investigating the role of emerging mitigation technologies and their uncertainties together with the different GHG reduction targets is crucial to realize this transition. This study analyzes the uncertainties of electric vehicles' learning paths and biomass availability for biofuels, considering policy uncertainties. Since these technologies are considered possible alternatives to conventional fuels to reduce CO2 emissions in transport, it is critical to understand their future role and the possible impact of their uncertainties during the European energy system design in case of different climate ambitions. Stochastic modeling is applied to analyze associated uncertainties as an additional approach to a traditional sensitivity analysis. Our results show that decarbonization of car transport is prioritized, and electric cars appear as no-regret options in the sector's design during the energy transition. Therefore, early deployments of EVs are essential to hedge the given uncertainties independent of the hedging period's length. Longer resolution time reduces the deployment of electric vehicles in the recourse strategies compared to having a shorter one due to a delay in the cost reductions. This decline becomes more evident with the stochastic analysis. The policy uncertainty of decarbonization targets has the highest impact on the studied uncertainties on the development of the transport sector. The transport sector can show faster adjustments considering the technology portfolio's shorter lifetime. Thanks to this adjustment, the sector depicts higher decarbonization in the hedging as well as in the recourse strategies.

The who, why and where of Norway’s [formula omitted] emissions from tourist travel

We present CO2 emissions from Norway’s tourist travel by the available transport modes, i.e., aviation, maritime (ferries and cruises) and land-based transport (road and railways). Our study includes detailed information on both domestic and international tourist travel within, from and to Norway. We have coupled statistics from several large surveys with detailed emission data to allow us to separate the purpose of the travel (holiday or business).Total transport CO2 emissions for tourists in 2018 were estimated to be 8 530 kt, equivalent to 19% of the reported Norwegian national CO2 emissions. Of these emissions, international tourists visiting Norway were responsible for 3 273 kt CO2, whereas travel by Norwegians accounted for 4 875 kt CO2, most of which occur outside Norway’s reporting obligations. Aviation and maritime transport were found to be the largest emission sources, responsible for 71% and 21% of total CO2 emissions, respectively. The reduction due to the COVID-19 pandemic was approximately 60% in 2020, and was sustained throughout the year.Our study shows that officially reported emissions, as limited to the countries territory, are not suitable for accurate evaluation of transport CO2 emissions related to tourism. A consumer or tourist-based calculation gives a marked redistribution of emission responsibility. Our results indicate that emissions from Norwegian residents travelling abroad are 1 602 kt higher than those from tourists coming to Norway. This is driven by frequent trips to popular tourist destinations such as Spain, Thailand, Turkey and Greece. Globally consumer based calculations would shift the responsibility of emissions by tourists to the large wealthy nations, with the most international tourists. The understanding of emission distributed by population group or market support in addition the developing of marketing strategies to attract low emission tourist markets and create awareness among the nations with higher shares of international tourist.